Determination of Characteristic Frequency for identification of Hot spots in Proteins using Computational Simulations: a Review

Sidhartha Sankar Sahoo^1, and Malaya Kumar Hota¹

¹Department of Electronics and Telecommunication Engineering, Synergy Institute of Engineering & Technology, Dhenkanal 759001, Odisha, India

Cite this paper:
Sidhartha Sankar Sahoo and Malaya Kumar Hota. Determination of Characteristic Frequency for identification of Hot spots in Proteins using Computational Simulations: a Review. American Journal of Computing Research Repository. 2014; 2(2):38-43. doi: 10.12691/ajcrr-2-2-3

Abstract

Proteins perform their functions by interaction with other molecules known as target. Protein-target interactions are very specific in nature and occur at predefined locations in proteins known as hotspots. For successful protein-target interaction both protein and target must share common spectral component known as characteristic frequency. Characteristic frequency is very importance since it forms basis for protein-target interactions, thus far various computational simulations have been used for determination of characteristics frequency. In this paper we have applied all computational simulations used till now and also use comparative study based on computational time and Signal to Noise Ratio parameter to stress the best suitable technique. All computational simulation works in this paper are done using MATLAB.

Keywords:
proteins amino acids Electron Ion Interaction Potential (EIIP) consensus spectrum resonant recognition model (RRM) characteristic frequency Discrete Fourier Transform (DFT) Chirp Z-Transform (CZT) Discrete Cosine Transform (DCT)

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References:

[1]	Alberts, B., Bray, D., Johnson, A., Lewis, J., Raff, M., Roberts, K., and Walter P., “Essential Cell Biology”, Garland Publishing, New York, 1998.
[2]	Bogan, A. A. and Thorn, K. S., “Anatomy of hot spots in protein interfaces”, Journal of Molecular Biology, 280 (1). 1-9. 1998.
[3]	Cosic, I., “Macromolecular bioactivity: is it resonant interaction between macro-molecules? - theory and applications”, IEEE Trans. on Biomedical Engr., 41 (12). 1101-1114. Dec. 1994.
[4]	Vaidyanathan, P. P. and Yoon, B.J., “The role of signal-processing concepts in genomics and proteomics”, Journal of the Franklin Institute, 341 (1-2). 111-135. 2004.
[5]	Ramachandran, P., Antoniou, A. and Vaidyanathan, P. P., “Identification and location of hot spots in proteins using the short-time discrete Fourier transform”, in Proc. 38th Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA. 1656-1660. Nov. 2004.
[6]	Ramachandran, P. and Antoniou, A., “Localization of hot spots in proteins using digital filters”, in Proc. IEEE Int. Symp. Signal Processing and Information Technology, Vancouver, BC, Canada. 926-931. Aug. 2006.
[7]	Ramachandran, P. and Antoniou, A., “Identification of Hot-Spot Locations in Proteins Using Digital Filters”, IEEE journal of selected topics in signal processing, 2 (3). June 2008
[8]	Sahu, S.S. and Panda, G., “Efficient Localization of Hot Spot in Proteins Using A Novel S-Transform Based Filtering Approach”, IEEE/ACM Transaction on Computational Biology and Bioinformatics, 8 (5). 1235-1246. 2011.
[9]	Kasparek, J., Maderankova, D. and Tkacz, E., “Protein Hotspot Prediction Using S-Transform. In Information Technologies in Biomedicine”, Springer International Publishing. 3. 327-336. 2014.
[10]	Sharma, A. and Singh, R., “Determination of Characteristic Frequency in Proteins using Chirp Z-transform”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2 (6). June 2013.
[11]	Proakis, J.G. and Manolakis, D.G., “Digital Signal Processing: principles, algorithms and applications ”, published by Pearson Education, Inc., © 2012
[12]	Sahoo, S.S. and Hota, M.K., “A Computational Simulation of Determination of Characteristic Frequency for Identification of Hot Spots in Proteins.” American Journal of Systems and Software, 2 (3). 81-84. 2014
[13]	Swiss-Prot Protein Knowledgebase. Swiss Inst. Bioinformatics (SIB). [Online]. Available: http://us.expasy.org/sprot/.
[14]	Protein Data Bank (PDB), Research Collaboratory for Structural Bioinformatics (RCSB). [Online]. Available: http://www.rcsb.org/pdb/.
[15]	Yadav, Y. and Wadhwani, S., “Identification of Characteristic frequency in Proteins using Power Spectral Density”, International Journal of Advances in Electronics Engineering, 1 (1). 342-346. 2011.